Beyond Deepfakes: Attestiv's DeepScan Redefines Digital Trust

LEHI, UT – July 08, 2026 – In an era where digital reality is increasingly fluid, the line between authentic and artificial has become dangerously blurred. Attestiv, a company at the forefront of digital media validation, today launched DeepScan, a platform that signals a critical evolution in how businesses must approach the rising tide of sophisticated fakes. This isn't just another deepfake detector; it's a fundamental shift from isolated forensic analysis to holistic, contextual validation, designed to restore trust in the very files that power modern enterprise.

The Eroding Foundation of Truth

The challenge is no longer theoretical. With some experts predicting that up to 90% of online content could be synthetically generated by 2026, the operational and financial risks are staggering. For industries like insurance, finance, and logistics, which rely on customer-submitted photos, documents, and videos, the threat is existential. Fraud, already a multi-billion-dollar problem for insurers, is being supercharged by generative AI tools that can create convincing forgeries with alarming ease.

This “truth crisis” extends beyond simple financial loss. It erodes customer trust, clogs operational pipelines with manual reviews, and opens the door to complex, multi-modal deception campaigns that combine fake images, audio, and documents to create a false but believable narrative. Until now, the primary defense has been detection—running a file through an algorithm to see if it has been manipulated. But as fakes become more sophisticated, this binary approach is proving insufficient.

“Deepfake detection has become a necessary part of validating customer-submitted files, but it is not sufficient on its own,” said Nicos Vekiarides, CEO of Attestiv, in today's announcement. The core problem, he argues, is that businesses need to answer a more complex question: not just is this file fake?, but can I trust this file for the specific decision I am about to make?

A New Architecture for Trust

This is the gap DeepScan is engineered to fill. Attestiv describes the platform as a “major architectural shift,” moving the goalposts from manipulation detection to business-level trustworthiness. It achieves this by pairing two powerful components: a generative AI reasoning layer and a dynamic, deterministic heuristic engine.

In simple terms, the platform doesn't just look for digital artifacts of manipulation. The AI reasoning layer is designed to understand context—cross-referencing file metadata and visual analysis against specific customer data and business rules. For example, it can check if the photo of a damaged car was taken at the location of the reported accident, or if the invoice date aligns with the transaction period. This contextual intelligence is what separates a simple forgery check from a true validation workflow.

Complementing this is the deterministic heuristic engine, which applies a consistent, configurable set of rules based on an organization's specific risk profile. Enterprise administrators gain granular control to set tolerances, thresholds, and automated actions—pass, flag, escalate, or request more information. This combination dramatically reduces the crippling false positives that plague many detection-only systems, allowing operations teams to focus on genuine anomalies rather than chasing digital ghosts.

The platform unifies this analysis across all major file types—photos, multi-page documents, audio, and video—under a single pane of glass. It integrates best-of-breed forensic signals, including a partnership with Google for AI content detection, within its broader validation framework, ensuring it can identify everything from simple Photoshop edits to advanced generative AI creations.

From Theory to Tangible ROI

While DeepScan is new, the principles behind it have already proven their value. Attestiv has been a quiet force in the fight against digital fraud for years, with its technology being used by fact-checkers like Misbar and PesaCheck to debunk viral disinformation and by insurance solution providers like Cabrella to proactively combat fraud in high-value shipping.

The most direct validation for DeepScan's approach comes from NARS, a leading claims management provider. “Since engaging Attestiv, NARS has benefited from Attestiv’s ability to help us stay ahead of an ever-changing fraud landscape,” stated Josiah Siegmund, SIU Unit Manager at NARS. He highlighted the platform's ability to identify “highly realistic forgeries,” which has enhanced their ability to prevent improper payments and strengthen the entire claims review process. This endorsement underscores the tangible ROI of moving from detection to contextual trust.

This impact is achieved through seamless integration. By offering robust APIs and SDKs, Attestiv allows its technology to be embedded directly into existing claims, risk, and compliance pipelines. This means businesses don't have to rip and replace their core systems; instead, they can augment them with a powerful new layer of automated trust, empowering human operators to make faster, more confident decisions.

The Regulatory Horizon

Attestiv's launch is timely, as regulators worldwide are beginning to catch up to the threat of AI-generated content. The EU AI Act, with its transparency mandates for deepfakes, and the NIST AI Risk Management Framework in the U.S. are creating a new compliance landscape. Businesses will soon be required not only to use AI responsibly but also to prove it.

Platforms like DeepScan are becoming essential tools for navigating this environment. By providing an auditable trail of how and why a file was validated, they offer a mechanism for accountability. This isn't about replacing human judgment but augmenting it with reliable, transparent, and context-aware intelligence.

As Attestiv rolls out DeepScan to its enterprise clients, it is offering more than a new product. It is presenting a forward-looking strategy for survival in an age of digital uncertainty. The platform's core premise—that trust is contextual—is a simple but profound insight that may prove to be the key to securing our digital future.